[GitHub] rahul003 commented on a change in pull request #11027: Add standard ResNet data augmentation for ImageRecordIter
rahul003 commented on a change in pull request #11027: Add standard ResNet data
augmentation for ImageRecordIter
URL: https://github.com/apache/incubator-mxnet/pull/11027#discussion_r203620309
##
File path: example/image-classification/common/data.py
##
@@ -63,6 +65,20 @@ def add_data_aug_args(parser):
help='max ratio to scale')
aug.add_argument('--min-random-scale', type=float, default=1,
help='min ratio to scale, should >= img_size/input_shape.
otherwise use --pad-size')
+aug.add_argument('--max-random-area', type=float, default=1,
+ help='max area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--min-random-area', type=float, default=1,
+ help='min area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--brightness', type=float, default=0,
Review comment:
@DickJC123 Hi Dick, I'm fixing these issues in
https://github.com/apache/incubator-mxnet/pull/11533
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[GitHub] rahul003 commented on a change in pull request #11027: Add standard ResNet data augmentation for ImageRecordIter
rahul003 commented on a change in pull request #11027: Add standard ResNet data
augmentation for ImageRecordIter
URL: https://github.com/apache/incubator-mxnet/pull/11027#discussion_r194191844
##
File path: example/image-classification/common/data.py
##
@@ -63,6 +65,20 @@ def add_data_aug_args(parser):
help='max ratio to scale')
aug.add_argument('--min-random-scale', type=float, default=1,
help='min ratio to scale, should >= img_size/input_shape.
otherwise use --pad-size')
+aug.add_argument('--max-random-area', type=float, default=1,
+ help='max area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--min-random-area', type=float, default=1,
+ help='min area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--brightness', type=float, default=0,
Review comment:
How about a function like the set_aug_level with the defaults set for
resnet, but that function is not automatically called?
My only concern was that we don't have a good source (for users not using
GluonCv, on a good set of starting params). Your point also makes sense, so am
not too strongly opinionated about this.
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[GitHub] rahul003 commented on a change in pull request #11027: Add standard ResNet data augmentation for ImageRecordIter
rahul003 commented on a change in pull request #11027: Add standard ResNet data
augmentation for ImageRecordIter
URL: https://github.com/apache/incubator-mxnet/pull/11027#discussion_r194191844
##
File path: example/image-classification/common/data.py
##
@@ -63,6 +65,20 @@ def add_data_aug_args(parser):
help='max ratio to scale')
aug.add_argument('--min-random-scale', type=float, default=1,
help='min ratio to scale, should >= img_size/input_shape.
otherwise use --pad-size')
+aug.add_argument('--max-random-area', type=float, default=1,
+ help='max area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--min-random-area', type=float, default=1,
+ help='min area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--brightness', type=float, default=0,
Review comment:
How about a function like the set_aug_level with the defaults set for
resnet, but that function is not automatically called?
My only concern was that we don't have a good source (for users not using
GluonCv, on a good set of starting params). Your point also makes sense, don't
have a strong opinion on this.
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[GitHub] rahul003 commented on a change in pull request #11027: Add standard ResNet data augmentation for ImageRecordIter
rahul003 commented on a change in pull request #11027: Add standard ResNet data
augmentation for ImageRecordIter
URL: https://github.com/apache/incubator-mxnet/pull/11027#discussion_r194190513
##
File path: example/image-classification/common/data.py
##
@@ -120,6 +136,7 @@ def get_rec_iter(args, kv=None):
else:
(rank, nworker) = (0, 1)
rgb_mean = [float(i) for i in args.rgb_mean.split(',')]
+random_resized_crop = args.random_resized_crop is not None
Review comment:
Also, for uniformity with random-crop and random-mirror we might want to
random-resized-crop be of type int
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[GitHub] rahul003 commented on a change in pull request #11027: Add standard ResNet data augmentation for ImageRecordIter
rahul003 commented on a change in pull request #11027: Add standard ResNet data
augmentation for ImageRecordIter
URL: https://github.com/apache/incubator-mxnet/pull/11027#discussion_r194186252
##
File path: example/image-classification/common/data.py
##
@@ -120,6 +136,7 @@ def get_rec_iter(args, kv=None):
else:
(rank, nworker) = (0, 1)
rgb_mean = [float(i) for i in args.rgb_mean.split(',')]
+random_resized_crop = args.random_resized_crop is not None
Review comment:
Wouldn't args.random_resized_crop never be None? action='store_true' means
if not passed it is set by default to false
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[GitHub] rahul003 commented on a change in pull request #11027: Add standard ResNet data augmentation for ImageRecordIter
rahul003 commented on a change in pull request #11027: Add standard ResNet data
augmentation for ImageRecordIter
URL: https://github.com/apache/incubator-mxnet/pull/11027#discussion_r194184683
##
File path: example/image-classification/common/data.py
##
@@ -63,6 +65,20 @@ def add_data_aug_args(parser):
help='max ratio to scale')
aug.add_argument('--min-random-scale', type=float, default=1,
help='min ratio to scale, should >= img_size/input_shape.
otherwise use --pad-size')
+aug.add_argument('--max-random-area', type=float, default=1,
+ help='max area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--min-random-area', type=float, default=1,
+ help='min area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--brightness', type=float, default=0,
Review comment:
I think it would be better to set defaults to the values we know work well,
so that this script is runnable easily. Especially since we no longer set the
aug level in train_imagenet.py
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[GitHub] rahul003 commented on a change in pull request #11027: Add standard ResNet data augmentation for ImageRecordIter
rahul003 commented on a change in pull request #11027: Add standard ResNet data
augmentation for ImageRecordIter
URL: https://github.com/apache/incubator-mxnet/pull/11027#discussion_r194184683
##
File path: example/image-classification/common/data.py
##
@@ -63,6 +65,20 @@ def add_data_aug_args(parser):
help='max ratio to scale')
aug.add_argument('--min-random-scale', type=float, default=1,
help='min ratio to scale, should >= img_size/input_shape.
otherwise use --pad-size')
+aug.add_argument('--max-random-area', type=float, default=1,
+ help='max area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--min-random-area', type=float, default=1,
+ help='min area to crop in random resized crop, whose
range is [0, 1]')
+aug.add_argument('--brightness', type=float, default=0,
Review comment:
I think it would be better to set defaults to the values we know work well
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[GitHub] rahul003 commented on a change in pull request #11027: Add standard ResNet data augmentation for ImageRecordIter
rahul003 commented on a change in pull request #11027: Add standard ResNet data augmentation for ImageRecordIter URL: https://github.com/apache/incubator-mxnet/pull/11027#discussion_r191026394 ## File path: src/io/image_aug_default.cc ## @@ -104,16 +127,37 @@ struct DefaultImageAugmentParam : public dmlc::Parameter
